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<a href="reduce_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/***************************************************************************************************</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2017-2019, NVIDIA CORPORATION.  All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * Redistribution and use in source and binary forms, with or without modification, are permitted</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> * provided that the following conditions are met:</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> *     * Redistributions of source code must retain the above copyright notice, this list of</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> *       conditions and the following disclaimer.</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> *     * Redistributions in binary form must reproduce the above copyright notice, this list of</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> *       conditions and the following disclaimer in the documentation and/or other materials</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> *       provided with the distribution.</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> *     * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *       to endorse or promote products derived from this software without specific prior written</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> *       permission.</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS &quot;AS IS&quot; AND ANY EXPRESS OR</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE</span></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,</span></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="comment"> * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;</span></div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> * OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,</span></div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> * STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE</span></div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment"> * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="comment"> **************************************************************************************************/</span></div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="cutlass_8h.html">cutlass/cutlass.h</a>&quot;</span></div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="numeric__types_8h.html">cutlass/numeric_types.h</a>&quot;</span></div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="array_8h.html">cutlass/array.h</a>&quot;</span></div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="half_8h.html">cutlass/half.h</a>&quot;</span></div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="functional_8h.html">cutlass/functional.h</a>&quot;</span></div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacecutlass.html">cutlass</a> {</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="keyword">namespace </span>reduction {</div><div class="line"><a name="l00039"></a><span class="lineno"><a class="line" href="namespacecutlass_1_1reduction_1_1thread.html">   39</a></span>&#160;<span class="keyword">namespace </span>thread {</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Op, <span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00043"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1thread_1_1Reduce.html">   43</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structcutlass_1_1reduction_1_1thread_1_1Reduce.html">Reduce</a>;</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00049"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01T_01_4_00_01T_01_4.html">   49</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structcutlass_1_1reduction_1_1thread_1_1Reduce.html">Reduce</a>&lt; <a class="code" href="structcutlass_1_1plus.html">plus</a>&lt;T&gt;, T &gt; {</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00052"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01T_01_4_00_01T_01_4.html#adc27a687496822f8477a427bf6ecd8b5">   52</a></span>&#160;  T <a class="code" href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01T_01_4_00_01T_01_4.html#adc27a687496822f8477a427bf6ecd8b5">operator()</a>(T lhs, T <span class="keyword">const</span> &amp;rhs)<span class="keyword"> const </span>{</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;    <a class="code" href="structcutlass_1_1plus.html">plus&lt;T&gt;</a> _op;</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    <span class="keywordflow">return</span> _op(lhs, rhs);</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;  } </div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;};</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> N&gt;</div><div class="line"><a name="l00062"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01T_01_4_00_01Array_3_01T_00_01N_01_4_01_4.html">   62</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structcutlass_1_1reduction_1_1thread_1_1Reduce.html">Reduce</a> &lt; <a class="code" href="structcutlass_1_1plus.html">plus</a>&lt;T&gt;, Array&lt;T, N&gt;&gt; {</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;  </div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00065"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01T_01_4_00_01Array_3_01T_00_01N_01_4_01_4.html#abb3c25f1d38931ffe40a24307fbf49b1">   65</a></span>&#160;  Array&lt;T, 1&gt; <a class="code" href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01T_01_4_00_01Array_3_01T_00_01N_01_4_01_4.html#abb3c25f1d38931ffe40a24307fbf49b1">operator()</a>(Array&lt;T, N&gt; <span class="keyword">const</span> &amp;in)<span class="keyword"> const </span>{</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    Array&lt;T, 1&gt; result;</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    <a class="code" href="structcutlass_1_1reduction_1_1thread_1_1Reduce.html">Reduce&lt; plus&lt;T&gt;</a>, T &gt; scalar_reduce;</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    result.clear();</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    <span class="keywordflow">for</span> (<span class="keyword">auto</span> i = 0; i &lt; N; ++i) {</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;      result[0] = scalar_reduce(result[0], in[i]);</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;    }</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;  }</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;};</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">int</span> N&gt;</div><div class="line"><a name="l00084"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01half__t_01_4_00_01Array_3_01half__t_00_01N_01_4_01_4.html">   84</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structcutlass_1_1reduction_1_1thread_1_1Reduce.html">Reduce</a> &lt; <a class="code" href="structcutlass_1_1plus.html">plus</a>&lt;<a class="code" href="structcutlass_1_1half__t.html">half_t</a>&gt;, Array&lt;<a class="code" href="structcutlass_1_1half__t.html">half_t</a>, N&gt; &gt; {</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;  </div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00087"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01half__t_01_4_00_01Array_3_01half__t_00_01N_01_4_01_4.html#afe8938d7e9d806511480831668ef1563">   87</a></span>&#160;  Array&lt;half_t, 1&gt; <a class="code" href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01half__t_01_4_00_01Array_3_01half__t_00_01N_01_4_01_4.html#afe8938d7e9d806511480831668ef1563">operator()</a>(Array&lt;half_t, N&gt; <span class="keyword">const</span> &amp;input) {</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    Array&lt;half_t, 1&gt; result;</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    <span class="comment">// If there is only 1 element - there is nothing to reduce</span></div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    <span class="keywordflow">if</span>( N ==1 ){</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;      result[0] = input.front();</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;    } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;    </div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;<span class="preprocessor">      #if defined(__CUDA_ARCH__) &amp;&amp; (__CUDA_ARCH__ &gt;= 600)</span></div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;        </div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;        __half result_d;</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;        Array&lt;half_t, 1&gt; <span class="keyword">const</span> *in_ptr_half = <span class="keyword">reinterpret_cast&lt;</span>Array&lt;half_t, 1&gt; <span class="keyword">const </span>*<span class="keyword">&gt;</span>(&amp;input);</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;        Array&lt;half_t, 2&gt; <span class="keyword">const</span> *in_ptr_half2 = <span class="keyword">reinterpret_cast&lt;</span>Array&lt;half_t, 2&gt; <span class="keyword">const </span>*<span class="keyword">&gt;</span>(&amp;input);</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;        __half2 <span class="keyword">const</span> *x_in_half2 = <span class="keyword">reinterpret_cast&lt;</span>__half2 <span class="keyword">const </span>*<span class="keyword">&gt;</span>(in_ptr_half2);</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;        <span class="comment">// Set initial result = first half2, in case N==2</span></div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;        __half2 tmp_result = x_in_half2[0];</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;        <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 1; i &lt; N/2; ++i) {</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;          tmp_result = __hadd2(x_in_half2[i], tmp_result);</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;        }</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;        </div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;        result_d = __hadd(__low2half(tmp_result), __high2half(tmp_result));</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;    </div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;        <span class="comment">// One final step is needed for odd &quot;N&quot; (to add the (N-1)th element)</span></div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;        <span class="keywordflow">if</span>( N%2 ){</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;          __half last_element;</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;          Array&lt;half_t, 1&gt; tmp_last;</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;          Array&lt;half_t, 1&gt; *tmp_last_ptr = &amp;tmp_last;</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;          tmp_last_ptr[0] = in_ptr_half[N-1];</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;          last_element = <span class="keyword">reinterpret_cast&lt;</span>__half  <span class="keyword">const </span>&amp;<span class="keyword">&gt;</span>(tmp_last);</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;          result_d = __hadd(result_d, last_element);</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;        } </div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;        Array&lt;half_t, 1&gt; *result_ptr = &amp;result;</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;        *result_ptr = <span class="keyword">reinterpret_cast&lt;</span>Array&lt;half_t, 1&gt; &amp;<span class="keyword">&gt;</span>(result_d);</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;<span class="preprocessor">      #else</span></div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;        </div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;        <a class="code" href="structcutlass_1_1reduction_1_1thread_1_1Reduce.html">Reduce&lt; plus&lt;half_t&gt;</a>, <a class="code" href="structcutlass_1_1half__t.html">half_t</a> &gt; scalar_reduce;</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;        result.clear();</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;        <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;        <span class="keywordflow">for</span> (<span class="keyword">auto</span> i = 0; i &lt; N; ++i) {</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;          result[0] = scalar_reduce(result[0], input[i]);</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;        }</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;<span class="preprocessor">      #endif</span></div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;    }</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;      </div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;  }</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;};</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">int</span> N&gt;</div><div class="line"><a name="l00158"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01half__t_01_4_00_01AlignedArray_3_01half__t_00_01N_01_4_01_4.html">  158</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structcutlass_1_1reduction_1_1thread_1_1Reduce.html">Reduce</a> &lt; <a class="code" href="structcutlass_1_1plus.html">plus</a>&lt;<a class="code" href="structcutlass_1_1half__t.html">half_t</a>&gt;, <a class="code" href="classcutlass_1_1AlignedArray.html">AlignedArray</a>&lt;<a class="code" href="structcutlass_1_1half__t.html">half_t</a>, N&gt; &gt; {</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;  </div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00161"></a><span class="lineno"><a class="line" href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01half__t_01_4_00_01AlignedArray_3_01half__t_00_01N_01_4_01_4.html#a37155e3dcc591e896df2d80c8daff4d4">  161</a></span>&#160;  Array&lt;half_t, 1&gt; <a class="code" href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01half__t_01_4_00_01AlignedArray_3_01half__t_00_01N_01_4_01_4.html#a37155e3dcc591e896df2d80c8daff4d4">operator()</a>(<a class="code" href="classcutlass_1_1AlignedArray.html">AlignedArray&lt;half_t, N&gt;</a> <span class="keyword">const</span> &amp;input) {</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;    Array&lt;half_t, 1&gt; result;</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;    <span class="comment">// If there is only 1 element - there is nothing to reduce</span></div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;    <span class="keywordflow">if</span>( N ==1 ){</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;      result[0] = input.front();</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;    } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;    </div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;<span class="preprocessor">      #if defined(__CUDA_ARCH__) &amp;&amp; (__CUDA_ARCH__ &gt;= 600)</span></div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;        </div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;        __half result_d;</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;        <a class="code" href="classcutlass_1_1AlignedArray.html">AlignedArray&lt;half_t, 1&gt;</a> <span class="keyword">const</span> *in_ptr_half = <span class="keyword">reinterpret_cast&lt;</span><a class="code" href="classcutlass_1_1AlignedArray.html">AlignedArray&lt;half_t, 1&gt;</a> <span class="keyword">const </span>*<span class="keyword">&gt;</span>(&amp;input);</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;        <a class="code" href="classcutlass_1_1AlignedArray.html">AlignedArray&lt;half_t, 2&gt;</a> <span class="keyword">const</span> *in_ptr_half2 = <span class="keyword">reinterpret_cast&lt;</span><a class="code" href="classcutlass_1_1AlignedArray.html">AlignedArray&lt;half_t, 2&gt;</a> <span class="keyword">const </span>*<span class="keyword">&gt;</span>(&amp;input);</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;        __half2 <span class="keyword">const</span> *x_in_half2 = <span class="keyword">reinterpret_cast&lt;</span>__half2 <span class="keyword">const </span>*<span class="keyword">&gt;</span>(in_ptr_half2);</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;        <span class="comment">// Set initial result = first half2, in case N==2</span></div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;        __half2 tmp_result = x_in_half2[0];</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;</div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;        <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 1; i &lt; N/2; ++i) {</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;          tmp_result = __hadd2(x_in_half2[i], tmp_result);</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;        }</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;        </div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;        result_d = __hadd(__low2half(tmp_result), __high2half(tmp_result));</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;    </div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;        <span class="comment">// One final step is needed for odd &quot;N&quot; (to add the (N-1)th element)</span></div><div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;        <span class="keywordflow">if</span>( N%2 ){</div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;          __half last_element;</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;          <a class="code" href="classcutlass_1_1AlignedArray.html">AlignedArray&lt;half_t, 1&gt;</a> tmp_last;</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;          <a class="code" href="classcutlass_1_1AlignedArray.html">AlignedArray&lt;half_t, 1&gt;</a> *tmp_last_ptr = &amp;tmp_last;</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;          tmp_last_ptr[0] = in_ptr_half[N-1];</div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;          last_element = <span class="keyword">reinterpret_cast&lt;</span>__half  <span class="keyword">const </span>&amp;<span class="keyword">&gt;</span>(tmp_last);</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;          result_d = __hadd(result_d, last_element);</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;</div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;        } </div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;        Array&lt;half_t, 1&gt; *result_ptr = &amp;result;</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;        *result_ptr = <span class="keyword">reinterpret_cast&lt;</span>Array&lt;half_t, 1&gt; &amp;<span class="keyword">&gt;</span>(result_d);</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;<span class="preprocessor">      #else</span></div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;        </div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;        <a class="code" href="structcutlass_1_1reduction_1_1thread_1_1Reduce.html">Reduce&lt; plus&lt;half_t&gt;</a>, <a class="code" href="structcutlass_1_1half__t.html">half_t</a> &gt; scalar_reduce;</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;        result.clear();</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;        <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;        <span class="keywordflow">for</span> (<span class="keyword">auto</span> i = 0; i &lt; N; ++i) {</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;          result[0] = scalar_reduce(result[0], input[i]);</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;        }</div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;</div><div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;<span class="preprocessor">      #endif</span></div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;    }</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;    <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;      </div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;  }</div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;};</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;}</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;}</div><div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;}</div><div class="ttc" id="namespacecutlass_html"><div class="ttname"><a href="namespacecutlass.html">cutlass</a></div><div class="ttdef"><b>Definition:</b> aligned_buffer.h:35</div></div>
<div class="ttc" id="half_8h_html"><div class="ttname"><a href="half_8h.html">half.h</a></div><div class="ttdoc">Defines a class for using IEEE half-precision floating-point types in host or device code...</div></div>
<div class="ttc" id="classcutlass_1_1AlignedArray_html"><div class="ttname"><a href="classcutlass_1_1AlignedArray.html">cutlass::AlignedArray</a></div><div class="ttdoc">Aligned array type. </div><div class="ttdef"><b>Definition:</b> array.h:511</div></div>
<div class="ttc" id="structcutlass_1_1half__t_html"><div class="ttname"><a href="structcutlass_1_1half__t.html">cutlass::half_t</a></div><div class="ttdoc">IEEE half-precision floating-point type. </div><div class="ttdef"><b>Definition:</b> half.h:126</div></div>
<div class="ttc" id="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01half__t_01_4_00_01AlignedArray_3_01half__t_00_01N_01_4_01_4_html_a37155e3dcc591e896df2d80c8daff4d4"><div class="ttname"><a href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01half__t_01_4_00_01AlignedArray_3_01half__t_00_01N_01_4_01_4.html#a37155e3dcc591e896df2d80c8daff4d4">cutlass::reduction::thread::Reduce&lt; plus&lt; half_t &gt;, AlignedArray&lt; half_t, N &gt; &gt;::operator()</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE Array&lt; half_t, 1 &gt; operator()(AlignedArray&lt; half_t, N &gt; const &amp;input)</div><div class="ttdef"><b>Definition:</b> reduce.h:161</div></div>
<div class="ttc" id="structcutlass_1_1plus_html"><div class="ttname"><a href="structcutlass_1_1plus.html">cutlass::plus</a></div><div class="ttdef"><b>Definition:</b> functional.h:46</div></div>
<div class="ttc" id="array_8h_html"><div class="ttname"><a href="array_8h.html">array.h</a></div><div class="ttdoc">Statically sized array of elements that accommodates all CUTLASS-supported numeric types and is safe ...</div></div>
<div class="ttc" id="cutlass_8h_html_a4b1c9f25ab6eaa25e1f2258dd63e6ce4"><div class="ttname"><a href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="ttdeci">#define CUTLASS_PRAGMA_UNROLL</div><div class="ttdef"><b>Definition:</b> cutlass.h:110</div></div>
<div class="ttc" id="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01T_01_4_00_01Array_3_01T_00_01N_01_4_01_4_html_abb3c25f1d38931ffe40a24307fbf49b1"><div class="ttname"><a href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01T_01_4_00_01Array_3_01T_00_01N_01_4_01_4.html#abb3c25f1d38931ffe40a24307fbf49b1">cutlass::reduction::thread::Reduce&lt; plus&lt; T &gt;, Array&lt; T, N &gt; &gt;::operator()</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE Array&lt; T, 1 &gt; operator()(Array&lt; T, N &gt; const &amp;in) const </div><div class="ttdef"><b>Definition:</b> reduce.h:65</div></div>
<div class="ttc" id="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01half__t_01_4_00_01Array_3_01half__t_00_01N_01_4_01_4_html_afe8938d7e9d806511480831668ef1563"><div class="ttname"><a href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01half__t_01_4_00_01Array_3_01half__t_00_01N_01_4_01_4.html#afe8938d7e9d806511480831668ef1563">cutlass::reduction::thread::Reduce&lt; plus&lt; half_t &gt;, Array&lt; half_t, N &gt; &gt;::operator()</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE Array&lt; half_t, 1 &gt; operator()(Array&lt; half_t, N &gt; const &amp;input)</div><div class="ttdef"><b>Definition:</b> reduce.h:87</div></div>
<div class="ttc" id="cutlass_8h_html_a28c2443a142676d3d71effdae1a986b1"><div class="ttname"><a href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="ttdeci">#define CUTLASS_HOST_DEVICE</div><div class="ttdef"><b>Definition:</b> cutlass.h:89</div></div>
<div class="ttc" id="numeric__types_8h_html"><div class="ttname"><a href="numeric__types_8h.html">numeric_types.h</a></div><div class="ttdoc">Top-level include for all CUTLASS numeric types. </div></div>
<div class="ttc" id="cutlass_8h_html"><div class="ttname"><a href="cutlass_8h.html">cutlass.h</a></div><div class="ttdoc">Basic include for CUTLASS. </div></div>
<div class="ttc" id="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01T_01_4_00_01T_01_4_html_adc27a687496822f8477a427bf6ecd8b5"><div class="ttname"><a href="structcutlass_1_1reduction_1_1thread_1_1Reduce_3_01plus_3_01T_01_4_00_01T_01_4.html#adc27a687496822f8477a427bf6ecd8b5">cutlass::reduction::thread::Reduce&lt; plus&lt; T &gt;, T &gt;::operator()</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE T operator()(T lhs, T const &amp;rhs) const </div><div class="ttdef"><b>Definition:</b> reduce.h:52</div></div>
<div class="ttc" id="functional_8h_html"><div class="ttname"><a href="functional_8h.html">functional.h</a></div><div class="ttdoc">Define basic numeric operators with specializations for Array&lt;T, N&gt;. SIMD-ize where possible...</div></div>
<div class="ttc" id="structcutlass_1_1reduction_1_1thread_1_1Reduce_html"><div class="ttname"><a href="structcutlass_1_1reduction_1_1thread_1_1Reduce.html">cutlass::reduction::thread::Reduce</a></div><div class="ttdoc">Structure to compute the thread level reduction. </div><div class="ttdef"><b>Definition:</b> reduce.h:43</div></div>
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